4 Reasons Organizations Use R for Data Analysis

Guest post by Adam Green.

“Analytics” is a real buzzword these days.

Whether you’re a marketer, a webmaster, or a CFO, you need data to stay competitive. And now that the tools used to gather data are more widely available and user-friendly than ever, there’s really no excuse not to use them.

But uses for analytical data transcend web activities, and many organizations use the R programming language to track a variety of undertakings. For the uninitiated, R is not a web application, but an expressive language used for data analysis. Even Google and Facebook use it to examine critical data and perform predictive modeling.

R, in fact, has emerged as one of the premier data analysis tools available. Here are 4 reasons why:

1. R is an open source project

Anyone can download R and start using it immediately The source code has been available for over 15 years, so today’s users benefit from a variety of expert improvements and modifications.

R also provides open interfaces that let it integrate with organizations’ existing systems. While third party R training and consulting services are available, the open source nature of R means that it is – and will remain – completely free.

2. R offers advanced graphical and visualization options

From bar graphs to scatterplots to graphics created by the user, R provides a flexible platform for visualizing data. Graphics created with R regularly appear in major media publications, the New York Times and the Economist being prime examples.

Simple visualization of data is actually one of the “founding principles,” so to speak, of the R platform.

3. R is infinitely extendable

Unlike applications that allow users to perform only a set number of functions, R can be modified to accomplish any data-gathering task. Because R users are always contributing code to the open source community, the functional possibilities are numerous.

For the truly ambitious, it’s also possible to connect R with other applications like MySQL databases and Apache servers. Even “mashing” R into the Google Analytics API is not out of the question.

4. R has a large community of users

As with many open source projects, a sizable community has grown up around R. Whenever you have a question about functionality, there are literally thousands of experienced users who can provide assistance.

Since R is a programming language – not a graphical “point-and-click” system – many may view it as an environment meant for only the most learned coders, but that’s not necessarily the case. R is actually among the easier programming languages to understand, and its numerous enthusiasts can help newbies make good use of it.

For web administrators who relish the “experience” of drilling deep into applications like Google Analytics, learning R could take that experience several steps further. An understanding of R will almost certainly provide a new – and more far-reaching – way to understand data.

This was a guest post by Adam Green, a freelance writer with a penchant for R training. When not working feverishly on client projects or narcissistically referring to himself in the third person, he can be found playing guitar on his front porch in Atlanta, Georgia.

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